RNA interference (RNAi) is an evolutionarily conserved defense mechanism against viral infections that can be harnessed to induce gene silencing (Merkling and van Rij, 2012, Wynant et al., 2017). Animal RNAi was first discovered in the nematode Caenorhabditis elegans (Fire et al., 1998). The specific degradation of mRNA is a method of silencing individual gene expression through a post-transcriptional mechanism, and RNAi has become the most widely used technique to induce gene-specific RNA degradation (Liu et al., 2014). Due to its conservation and specificity, RNAi has been extensively employed for gene silencing in various eukaryotic systems (Price and Gatehouse, 2008, Ketting et al., 2001, Shukla et al., 2016).
In recent years, RNAi that is based on the application of homologous double-stranded RNA (dsRNA) molecules, has shown great potential as a biological pesticide for the selective control of agricultural pests (Baum et al., 2007, Zhu et al., 2011, Spit et al., 2017, Zhu and Palli, 2020, Taning et al., 2021, Narva et al., 2025). RNAi can specifically target pests without harming non-target or beneficial organisms, such as pollinators and parasitoid wasps used in biological control, which offers significant opportunities in insect science, particularly in gene function analysis through reverse genetics (Bettencourt et al., 2002, Liu et al., 2013), pest population management (Baum et al., 2007), and the suppression of disease pathogens (Garbian et al., 2012). In agricultural biotechnology, insecticides based on gene-specific dsRNA represent a promising strategy for pest control (Baum et al., 2007, Price and Gatehouse, 2008, BELLES, 2010; San Miguel and Scott, 2016, Zhang et al., 2017).
However, challenges remain in the application of RNAi for pest control, with the primary limitation being the efficient delivery of the RNAi trigger, i.e., dsRNA molecules. Only intact dsRNA that reaches the target site and maintains long-term stability in tissues, enabling cellular uptake into the cytoplasm, where the core RNAi machinery resides, can effectively induce RNAi (Peng et al., 2018). The variable effectiveness of RNAi across different organisms poses significant constraints on its use in functional insect research (Cooper et al., 2019, Howell et al., 2020, Quilez-Molina et al., 2024).
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